Since clinical CT images with the whole abdominal region are very private and hard to collect and annotate, the openly available datasets are very few. We summary these publicly available abdominal CT datasets in Tab. REF , we just consider these datasets which have four or more organs are annotated in this work. The BTCV (Beyond The Cranial Vault) [1]} consists of 50 CT volumes, where 30 and 20 volumes are used for training and testing, respectively. In the BTCV dataset, 13 organs are annotated manually, including the aorta, liver, spleen, right kidney, left kidney, stomach, pancreas, gallbladder, esophagus, inferior vena cava, portal vein and
splenic vein, right adrenal gland, and left adrenal gland. The DenseVNet [2]} has 90 CT scans, where 47 scans come from the BTCV dataset [1]} and the other 43 cases come from TCIA data [4]}. There are 8 organs are annotated by a radiologist. The CT-ORG [5]} is an open dataset which contains 140 CT images and 6 organs are annotated, most of these images come from a challenge training set [6]}. The AbdomenCT-1K dataset [7]} extended five open single-class organs annotation datasets to four classes (with 1062 volumes) and a small clinical dataset (with 50 volumes come from 20 patients). This dataset contains four organs annotations, containing liver, kidney, spleen, and pancreas. BTCV, DenseNet, and CT-ORG are limited by the small scale or few annotated classes to boost this topic research. Although AbdomenCT-1K is very huge, the annotated organs are also too few to evaluate the efficiency of the whole abdominal segmentation task. Different from these existing datasets, our dataset comes from a new medical center and has a large scale and more annotated organs. We believe that this dataset is one of the most comprehensive ones in medical image segmentation datasets.
